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Upside

Cash-back app for everyday retail purchases

Analytics Engineer - Data Platform

Data EngineeringConfirmed live in the last 24 hours
Full-timeHybrid

About the Job

Requirements

  • Around 3–5 years of experience in data or analytics engineering, or comparable work under a different title.
  • Fluency in SQL, including window functions and complex joins, and the ability to consider query performance.
  • Experience owning dbt models in a version-controlled repository, including conventions, tests, continuous integration, and occasional cleanup of existing work.
  • Working knowledge of Python for orchestration, transformations, and tests.
  • Ability to explain modeling tradeoffs, such as dimensional modeling versus one big table, and justify a choice.
  • Ability to explain technical decisions to marketing and engineering audiences and tailor communication to each.
  • Experience with Snowflake or a comparable data warehouse.

Responsibilities

  • Own a scoped domain of dbt models by designing, building, testing, shipping, and monitoring them, and determining how they should be structured.
  • Turn ambiguous requests from Marketing and Product into scoped work and discuss tradeoffs when requests and timelines conflict.
  • Write design documents for owned features and break work into pieces teammates can take on.
  • Add monitoring and alerting to models so the team can catch problems before stakeholders do.
  • Participate in the support rotation, debug failures, and prevent recurrence.
  • Create runbooks, schema documentation, and diagrams to enable others to own the work.
  • Coach less experienced engineers on the team through code review and day-to-day guidance.

Desired Qualifications

  • Experience with marketing, growth, or lifecycle data, including events, attribution, experimentation, or tools such as Braze, Iterable, or Segment.
  • Experience with Dagster, Airflow, or another modern orchestrator.
  • Experience with continuous integration and continuous delivery for data, data governance, or cost-conscious warehouse design.
  • Experience supporting machine-learning workflows, such as building features or monitoring model inputs.
  • Experience making warehouse data usable by artificial-intelligence tooling, including semantic layers, data contracts, or documentation readable by agents and people.

About the Company

Upside

Cash-back app for everyday retail purchases

Upside runs a cash-back app for everyday retail. Users open the app, claim nearby cashback offers, and then shop at gas stations, groceries, and food outlets as usual to earn money back. The app generates revenue by partnering with retailers and brands that pay commissions for driving traffic and sales, and a portion of that commission is shared with users as cashback. What sets Upside apart is its focus on a wide network of nearby, essential-purchase retailers and its emphasis on privacy, sustainability, and inclusive company culture. Upside aims to level the playing field in brick-and-mortar commerce by increasing consumers' purchasing power while helping retailers boost loyalty and profits.

Company size
201-500
Company stage
Debt Financing
Total funding
$165M
Headquarters
Washington DC, District of Columbia
Founded
2015

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